To register, please send email to researchservices@bc.edu with the names of the tutorials that you are interested in attending.

Creating Path Models with SPSS and Stata

This tutorial will explore the basic steps in understanding the terminology of path models for use in the social sciences. Path Models are also described as causal modeling, and is an important aspect of Structuring Equation Modeling in the social sciences. The goal of this session is to introduce some concepts of path modeling which can then be applied to more advanced statistical analysis.

October 1, 2008  12:00 pm – 1:00  pm, O’Neill 245

Creating Web-based Surveys with Survey Monkey

Survey Monkey offers a way to create surveys without complicated programming or coding. Working within pre-defined templates, you can use several different types of questions, including text, multiple checkboxes, single-answer radio buttons, Likert scales. Once the survey is completed, data can be downloaded into a format that can be used with Excel, SPSS, or other analysis programs. Research Services Staff are also available, upon request, to schedule follow up consultations regarding analysis of your online survey data once the data has been collected.

October 16, 2008  2:00 pm – 3:30 pm, Gasson 9

Demographic analysis with ArcGIS: Geostatistics

The focus of this workshop will be on the use of ArcGIS to analyze demographic data. The session will highlight GIS data available for research and include demonstrations of ArcGIS using cases based on Census and related data. GIS is an analysis tool which complements other quantitative methods used to analyze population data. The data that the Census Bureau collects during the decennial census and other population surveys has grown extensively over the years and has become an important resource for researchers and government agencies. Besides providing the basis for congressional redistricting, Census data are used in many other ways. Since 1975, the Census Bureau has had responsibility to produce small-area population data needed to redraw state legislative and congressional districts. Other important uses of Census data include the distribution of funds for government programs; planning the right locations for schools, roads, and other public facilities; helping real estate agents and potential residents learn about a neighborhood; and identifying trends over time that can help predict future needs. Most Census data are available for many levels of geography, including states, counties, cities and towns, ZIP codes, census tracts and blocks.

Census data and GIS applications are used by community planners, marketing, managers, scientists and researchers in education, economists, sociologists, social workers, health care managers, librarians, and data administrators.

International population data are available also to address demographic issues in a specific country, at regional or at global scale. We will discuss these resources with those interested. No prior knowledge of ArcGIS is required.

September 25, 2008  10:00 am - 11:30 am,  O’Neill 245 

Getting Started with HLM 6

This tutorial will explore the basic concepts involved in applying hierarchical linear modeling using HLM6. Particular focus will be placed on understanding how heteroskedastic errors may occur when using ordinary least squares for analysis, and how the method of mixed modeling may be able to account for this problem in the social sciences using HLM6. We will cover the creation of a multivariate data matrix (mdm) file using the software, and proceed to generating results for a null model along with calculating the Intraclass Correlation Coefficient.

October 15, 2008  12:00 pm – 1:00 pm, O’Neill 245

Getting Started with SPSS 16

SPSS 16 is a powerful and yet easy to use statistical package. This hands-on tutorial is designed as an introduction for beginning users who are just getting started using SPSS. The following topics will be covered:

• Getting started with SPSS
• Creating and importing data files
• Descriptive statistics
• Creating variablesLabeling variables and values
• Using the SPSS 15 Legacy Viewer for Windows to read output from older releases

September 25, 2008  2:00 pm – 3:30 pm, Gasson 9

Introduction to ArcGIS

Geographic Information Systems (GIS) are used today to analyze and represent data with geographical reference on maps. Such applications are widely used in academia, private industry and government agencies and the number of applications is increasing. ArcGIS Desktop software products from the Environmental Research Systems Institute (ESRI).

ArcGIS Desktop is an integrated suite of advanced GIS applications and interfaces, including ArcMap, ArcCatalog, ArcGlobe, ArcScene, ArcToolbox, and ModelBuilder. Using these applications and interfaces, you can perform any GIS task, from simple to advanced, including mapping; geographic analysis; data editing, compilation, and management; visualization; and geoprocessing. ArcGIS Desktop is scalable to meet the needs of many types of users.

This session will introduce users to: 1) GIS software, data and technical support at Boston College; 2) License options; 3) Main ArcGIS features and capabilities (ArcMap, ArcCatalog, ArcTool, ArcGlobe); 4) Present available extensions and capabilities (Spatial Analyst, Geostatistical Analyst, etc); 5) Demos using Census data; Demos using Environmental data. Options to get data and training will be also discussed. No prior knowledge of ArcGIS is required.

September 18, 2008  10:00 am - 11:30 am,  O’Neill 245   

Introduction to Mathematica

The goal of this hands–on seminar is to introduce beginning level users to Mathematica computing system. No previous experience with Mathematica is necessary, while some background in Calculus and Algebra will be helpful. The software is now used worldwide in academia, industry and government research labs and has a complete environment for technical computing tasks, whether simple calculations or large-scale computations, complex programming, visualizing or modeling data. Boston College has a site license and many faculty, staff and students are using Mathematica for research, teaching and learning. We will demonstrate topics related to use of documentation, help, notebooks, Mathematical functions, Visualization and Graphics, and new capabilities in Mathematica 6.0.

October 2, 2008  2:00 pm- 4:00 pm, O’Neill 245 

MATLAB 1: Introduction to Matlab programming

MATLAB fundamentals provide a working introduction to the MATLAB technical computing environment. Matlab can be used with all aspects Mathematical computation, analysis, visualization, and algorithm development. This course is intended for beginning and intermediate users. No prior knowledge of MATLAB is required. Familiarity with a programming language (Fortran, C for example) will be helpful. Themes of vector and matrix data analysis, graphical visualization, data modeling, and MATLAB programming are explored in the context of realistic examples.

This Matlab hands-on practice workshop will present:

• Introduction: The Matlab system; Matlab documentation and help; Starting and quitting Matlab; How to use Matlab on Linux cluster “scorpio”
• Matrices and arrays:  Entering matrices; Load data; Matrix Algebra
• Matlab programming: Program control statements; Data types; Variables; Operators; Expressions; Matlab functions; Creating a program; Importing and exporting text and Excel data
• Introduction to Matlab graphics capabilities

October 9, 2008  10:00 - 11:30, O’Neill 245 

MATLAB 2: Graphs and Visualization

The type of graph needed in a specific project depends on the nature of available data and on what is intended to reveal about the data. MATLAB predefines many graph types,  such as line, bar, histogram, and pie graphs. There are also 3-D graphs, such as surfaces, slice planes, and streamlines.  There are two basic ways to create graphs in MATLAB: 1) Use plotting tools to create graphs interactively; 2) Use the command interface to enter commands in the Command Window or create plotting programs (m files).

This Matlab hands-on practice workshop will focus on m-files to produce graphics, data visualization, and animation. We will show:

• Basic Plotting Commands: Commands Plotting Steps; Creating Line Plots
  Specifying Line Style; Colors, Line Styles, and Markers; Specifying the Color and Size of Lines; Adding Plots to an Existing Graph; Plotting Only the Data Points; Plotting Markers and Lines; Line Styles for Black and White Output; Samples of various 2D plots
• Figure Windows: Displaying Multiple Plots per Figure; Subplots; Save and print plots
• Samples of 3D Plots
• Animation:  Movies; Erase Modes; Examples on how to create animations

Examples presented (m files) can be easily modified and applied to your specific  experimental or model data.

October 16, 2008  10:00 - 11:30, O’Neill 245 

MATLAB 3: Statistics

This MATLAB hands-on practice workshop with focus on statistical toolbox and illustrate some of the methods used in univariate, and bivariate. The objective is to learn to work with data in the MATLAB environment, compute basic descriptive statistics, and visualize data in a variety of ways. It is assumed that participants have already some knowledge of  MATLAB  (at the level of previous two workshops) and background in Applied Statistics.

• Descriptive statistics: Measures of center, spread, and shape
  Statistical plotting: Histograms, scatter plots, and box plots
• Review the basics of probability and random variables and explore the variety of probability distributions available in the Statistics Toolbox.
• Random variables, Sampling distributions, Bootstrapping
• Explore regression analysis for bivariate data:Regression concepts,
  Linear and nonlinear models, Scatter plots, Correlation and covariance
• Linear least squares. Polynomial fitting. 
• Graphical user interface tools for linear regression   

October 23, 2008  10:00 - 11:30, O’Neill 245 

MATLAB 4: Multivariate statistics

This MATLAB hands-on practice workshop with focus on and multivariate statistics.  The objective is to learn to work with data in the MATLAB environment, to perform statistical analysis of data sets with multiple variables. One of the difficulties inherent in multivariate statistics is the problem of visualizing data that has many variables. Fortunately, in data sets with many variables, groups of variables often move together. One reason for this is that more than one variable might be measuring the same driving principle governing the behavior of the system.  When this happens, you can take advantage of this redundancy of information. You can simplify the problem by replacing a group of variables with a single new variable. Principal components analysis is a quantitatively rigorous method for achieving this simplification.

Topics illustrated:

• Multivariate statistics: Principal Components Analysis, The Principal Component Coefficients, The Component Scores, The Component Variances,
• Visualizing the Results of a Principal Components Analysis.
• Factor analysis. Multivariate regressions and special graphics methods to visualize the relationships between many variables.

It is assumed that participants have already some knowledge of  MATLAB  (at the level of previous workshops) and background in Applied Statistics.

October 302008  10:00 - 11:30,  O’Neill 245 

MATLAB 5: Linear Algebra

This MATLAB workshop will focus on Linear Algebra. MATLAB was originally designed for linear algebra computations and therefore provides a rich environment for dealing with linear equation systems and eigenvalue problems.
The objective is to learn how to solve linear equation systems in an efficient way, to deal with matrix factorizations and decompositions and to solve eigenvalue problems. It is assumed that participants have already some knowledge of MATLAB  (at the level of previous workshops) and background in Linear Algebra.

The topics that will be covered are:

• Norm and Condition numbers
• Linear Equation systems (square, overdetermined and underdetermined)
• Inverse
• Pseudo-Inverse
•  Determinant
•  LU and Cholesky Factorizations, QR Factorization
•  Singular Value Decomposition
• Eigenvalue problems, Generalized Eigenvalues
•  Iterative Linear Equation and Eigenproblem Solvers
•  Functions of a matrix.

November 3, 2008  10:00 am - 11:30 am,  O’Neill 245 

MATLAB 6: Numerical Methods, Part I

This MATLAB workshop will start a two-meeting session on Numerical Methods.
In this first meeting we will deal with functions that allow for the solution of problems involving polynomials, nonlinear equations, and optimization.
It is assumed that participants have already some knowledge of MATLAB (having a grasp on how to deal with MATLAB functions would be beneficial) and background in statistics (Data fitting) and optimization theory.

The topics that will be covered are: Polynomials (Evaluation, Root finding and Data fitting), Nonlinear equations, Optimization.

November 10, 2008, 10:00 am - 11:30 am, O’Neill 245 

MATLAB 7: Numerical Methods, Part II

This MATLAB workshop will conclude a two-meeting session on Numerical Methods. In this second meeting we will deal with integrals evaluation and with the solution of ordinary differential equations. Given the more advanced nature of these topics, more time will be spent on examples and exercises to help the understanding of the material.

It is assumed that participants have already some knowledge of MATLAB (having a grasp on how to deal with MATLAB functions would be beneficial) and background in integral calculus and system dynamics.

The topics that will be covered are: Quadrature, Ordinary Differential Equations (ODE), Stiff ODE.

November 19, 2008  10:00 am - 11:30 am, O’Neill 245

Secondary Research Data Resources At Boston College

 Boston College offers many sources and repositories of data for secondary research in the social sciences, education, nursing, economics, business and other disciplines.  This workshop is particularly geared to researchers who need to access, analyze and manipulate data from BC's subscription data repositories.  This tutorial will help you: find the data you need for your research or class project; learn about the Boston College collection of data resources in the Statistical Data Catalog; and how to download the data onto your desktop, including how to import into quantitative analytical tools such as SPSS.  Get a tour of the Inter-University Consortium for Political and Social Research, a data archive that includes over 5,000 datasets. We will also discuss the library’s guides to key Business, Economics, Education, Health, and General U.S. and cross-national data sources. Topics may be customized based on attendees’ research interests.

October 23, 2008  2:00 pm – 3:30 pm, Gasson 9 

Stata 1: Getting Started with Stata

Stata is a powerful and yet easy to use statistical package. This hands-on tutorial is designed as an introduction for beginning users who are just getting started using Stata. The following topics will be covered:

• Getting started with Stata
• Creating and using "log" files
• Descriptive statistics
• Creating variables
• Labeling variables and values

September 24, 2008  12:00 pm – 1:00 pm, O’Neill 245  

Stata 2: Regression Analysis, Odds Ratio, Discrete and Marginal Effects

This hands-on tutorial is designed as an introduction for beginning users who already know the basics of Stata. The following topics will be covered:

• Probit regression analysis
• Logistic regression analysis
• Odds ratio
• Discrete and marginal effects

October 29, 2008, 12:00 pm – 1:00 pm, O’Neill 245

Stata 3: Running Stata on the Scorpio Linux Cluster

This hands-on tutorial is designed as an introduction for users who knows basics of Stata. The tutorial will cover how to run Stata do-files using the Scorpio Linux Cluster. There are two 4-processor licenses of Stata (stata-mp) for the Scorpio Linux Cluster.  These licenses can be used for large and long running Stata applications. You can find more information about the cluster from and how to get an account from: www.bc.edu/offices/researchservices/cluster.html .

November 12, 2008  12:00 pm – 1:00 pm, O’Neill 245

Using Multivariate Regression Modeling on SPSS and Stata

This tutorial will cover the steps in using variables for regression modeling with SPSS in the social sciences. A discussion on the basic assumptions of linear regression, how to begin to describe social phenomenon, and understanding the language of the software will be presented for intermediate learners. Processes in transforming variables, interpreting the F-statistic, significance, and ranking regressors will be explored using procedures with SPSS and Stata.

September 29, 2008, 12:00 pm – 1:00 pm, O’Neill 245

Using a Scale: Reliability Analysis and Factor Analysis on SPSS

This tutorial will cover the basic steps involved in getting a Cronbach's Alpha on a set of variables for use as a scale, and interpreting the results in SPSS. Additionally, exploratory factor analysis will be discussed to determine dimensions within a scale that can be assessed for validity.

November 19, 2008  12:00 pm – 1:00 pm, O’Neill 245